Government tenders £10m for AI tool aiming for near-instant planning decisions
The government has issued a £10 million tender to build an AI "planning tool" to support AI-augmented decision making on planning applications. The initial scope targets householder developments with a long-term ambition of near-instant decisions, subject to legal and policy checks.
For planning authorities, this signals a shift toward decision support at scale. The goal: reduce routine workload, speed up determinations, and increase consistency-while keeping officers in control.
What this could mean for planning teams
- Faster validation and triage for householder applications (completeness checks, fee validation, basic constraints).
- Standardised policy screening against local plans and national guidance.
- Evidence packs for officers: site context, constraints, and comparable decisions.
- Draft officer reports and conditions that you can edit, not accept blind.
- Clear audit trails to show how a recommendation was formed.
Guardrails you should insist on from day one
- Human-in-the-loop: officers approve every recommendation; no automatic determinations.
- Explainability: the tool must show the policy sources, data, and steps behind each suggestion.
- Audit and FOI readiness: immutable logs, versioning of models and prompts, and exportable reports.
- Bias testing: monitor outputs for consistency across wards, demographics, and application types.
- Privacy and security: DPIA, data minimisation, access controls, and clear data retention rules.
- Policy updates: rapid updates when the NPPF or local plan policies change.
Integration and data: make or break
The tool will only help if it fits your stack. Expect the need for clean address data, UPRNs, GIS layers, and integration with your back-office system and the planning portal.
- APIs for case data, constraints, and document retrieval.
- Consistent schema for application types, statuses, and decisions.
- Clear separation between training data, operational data, and public outputs.
Practical procurement checklist
- Scope: start with householder applications; define exclusions (e.g., listed buildings if you choose).
- KPIs: validation time saved, officer hours reclaimed, decision consistency, and user satisfaction.
- Pilots: phased rollout with A/B testing against current process.
- Legal: DPIA, data processing clauses, intellectual property, and an exit plan with data portability.
- Model governance: model provenance, update cadence, and incident response if outputs are challenged.
- Pricing: avoid lock-in; check costs for usage spikes and storage.
Risks to manage early
- Over-reliance: the tool should assist, not decide. Reinforce officer judgement and local context.
- Fairness: monitor variance across areas and applicant profiles; publish methods for scrutiny.
- Drift: as policy or data changes, ensure outputs stay aligned with the latest guidance.
- Public trust: be transparent about where AI is used in the workflow and how to challenge decisions.
How to prepare your authority now
- Map the current householder workflow and identify decision pain points.
- Standardise report templates, conditions, and validation lists.
- Clean key datasets (UPRNs, constraints layers, historic decisions) and fix common data errors.
- Agree success metrics and a feedback loop for officers and applicants.
- Upskill your team on AI literacy and oversight practices. If helpful, explore role-based options at Complete AI Training.
Standards and guidance worth bookmarking
The tender sets a clear direction: use AI to clear the backlog and improve service without giving up accountability. Start with strong governance and clean data, and the benefits will show up in weeks, not years.
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